Optimal pricing of endogenous congestion: a disaggregated approach.

We design and estimate a game theoretic congestion pricing mechanism in which the regulator aims at reducing urban traffic congestion by price discriminating travelers according to their Value Of Time (VOT). Travelers' preferences depend on their observable characteristics, on the endogenous amount of congestion anticipated, on their Marginal Utility (MU) of income and on some unobserved factors. Using a French household survey, we estimate the demand models to simulate different pricing mechanisms. We find that unobserved determinants of transportation demand are significant and are used to measure the anticipated time spent in traffic and the comfort of traveling: diverging from these expectations is felt as more discomfort than if no expectations were formed a-priori. However some of this discomfort is derived from travelers' marginal utility of income: the lost time in traffic is clearly "unpleasant" because of its opportunity cost. When the regulator and the transportation provider share common objectives, we show that a great welfare improvement can be achieved when implementing a homogenous pricing that accurately accounts for travelers VOT.regulatory policy; endogenous congestion; incomplete information; reputation effects, welfare simulation

Choice Valuation of Traffic Restrictions: Perspectives on Noise, Pollution and Congestion Preferences

This paper focuses on the choice valuation of traffic restrictions while entering Lisbon city based on individual preferences for noise, pollution and congestion. The analysis employs a questionnaire distributed in 2007 to ascertain the significant characteristics of traveling to Lisbon, with the aim of curbing the number of cars that enter the city daily. A random parameter logit model is used to analyze the characteristics (e.g. individual characteristics, motivations, type of transport used) that are associated with the probability of individuals supporting a fee on private cars entering the city. The model also takes into account the uncontrolled heterogeneity of the data. Some policy implications are also presented.Transportation; Lisbon; Mixed Logit Model; Public Policy.

US Highway Privatization and Heterogeneous Preferences

Abstract: We assess the welfare effects of highway privatization accounting for government’s behavior in setting the sale price, firms’ strategic behavior in setting tolls in various competitive environments, and motorists’ heterogeneous preferences for speedy and reliable travel. We conclude motorists can benefit from privatization if they are able to negotiate aggressively with a private provider to obtain tolls and service that align with their varying preferences. Surprisingly, motorists are likely to be better off negotiating with a monopolist than with duopoly providers or under public-private competition. Toll regulation may be counterproductive because it would treat motorists as homogeneous. Revised June 2009.Security Breach Costs; Financial Distress; Insurance; Resource Allocation.

Differentiated Road Pricing, Express Lanes and Carpools: Exploiting Heterogeneous Preferences in Policy Design

In the face of rising congestion on the nation's road system, policymakers have explored ways to reduce travel delays. One approach has been to allocate reserved lanes, called high-occupancy-vehicle (HOV) lanes, to vehicles carrying two or more people. A recent innovation is to allow solo drivers to use the HOV lanes if they pay a toll. These so-called high-occupancy-toll (HOT) lanes can be found in Los Angeles, San Diego, Houston, and Minneapolis and are under consideration in several other urban areas. In this paper, we argue that HOV and HOT lanes sacrifice efficiency by failing to price all lanes.Moreover, we show that it is possible to set prices on all lanes that improve on the efficiency of HOV and HOT policies and by catering to motorists' varying preferences, can meet the test of political acceptability.

Housing Price Gradients in a Region with One Dominating Center

This paper primarily focuses on predicting housing price gradients in a Norwegian region with one dominating center. Spatial separation is represented by a function of the traveling distance from the city center in a traditional hedonic regression equation. Several functions are tested, and some alternatives provide a satisfying goodness-of-fit, consistent coefficient estimates, and intuitively reasonable predictions of housing price gradients. Still, not all commonly used functions are recommended. The findings also indicate that the strength of spatial autocorrelation is reduced when the hedonic function is properly specified.